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71.
Wang Yi-Ting Shen Jie Li Zhi-Xu Yang Qiang Liu An Zhao Peng-Peng Xu Jia-Jie Zhao Lei Yang Xun-Jie 《计算机科学技术学报》2020,35(4):724-738
Journal of Computer Science and Technology - Entity linking (EL) is the task of determining the identity of textual entity mentions given a predefined knowledge base (KB). Plenty of existing... 相似文献
72.
Yong Xu Yun Li Songlin Li Francis Balestra Gerard Ghibaudo Wenwu Li Yen‐Fu Lin Huabin Sun Jing Wan Xinran Wang Yufeng Guo Yi Shi Yong‐Young Noh 《Advanced functional materials》2020,30(20)
Unreliable mobility values, and particularly greatly overestimated values and severely distorted temperature dependences, have recently hampered the development of the organic transistor field. Given that organic field‐effect transistors (OFETs) have been routinely used to evaluate mobility, precise parameter extraction using the electrical properties of OFETs is thus of primary importance. This review examines the origins of the various mobilities that must be determined for OFET applications, the relevant extraction methods, and the data selection limitations, which help in avoiding conceptual errors during mobility extraction. For increased precision, the review also discusses device fabrication considerations, calibration of both the specific gate‐dielectric capacitance and the threshold voltage, the contact effects, and the bias and temperature dependences, which must actually be handled with great care but have mostly been overlooked to date. This review serves as a systematic overview of the OFET mobility extraction process to ensure high precision and will also aid in improving future research. 相似文献
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74.
Nazir Kizzie‐Hayford Doris Jaros Yvonne Schneider Harald Rohm 《International Journal of Food Science & Technology》2015,50(2):381-388
A standard method for the extraction of tiger nut milk has been introduced. It has been shown that, although milling duration improves the yield of tiger nut milk solids and its nutrient composition, there is a quantifiable loss of nutrient in the pressing residue during milk extraction. Milling duration improved the colloidal stability of the milk against creaming during 16 h of storage. A higher milling intensity resulted in the aggregation of biological polymers which resulted in colloidal destabilisation. Milling improved the lightness and stability and reduced browning rate of the tiger nut milk during storage. This report is important for the production of tiger nut milk of consistent and comparable characteristics. Milling has been introduced as a processing method for the qualitative and quantitative modulation of the properties of tiger nut milk. It is recommended to develop further strategies to improve the colloidal stability of tiger nut milk as a beverage. 相似文献
75.
Study on the self‐assembly property of type I collagen prepared from tilapia (Oreochromis niloticus) skin by different extraction methods 下载免费PDF全文
Mingyan Yan Song Qin Jie Li 《International Journal of Food Science & Technology》2015,50(9):2088-2096
Type I collagen was prepared from tilapia (Oreochromis niloticus) skin by acetic acid and pepsin process at 4 °C, respectively (ASC and PSC), and hot‐water method separately at 25, 35 and 45 °C (C‐25, C‐35 and C‐45). Their structure and self‐assembly property were discussed. SDS‐PAGE patterns suggested that pepsin hydrolysis and the 35 and 45 °C extraction produced collagen with much reduced proportions of α‐ and β‐chains. Fourier transform infrared spectroscopy spectra revealed that pepsin hydrolysis did not change the conformation of collagen, but higher extraction temperature did. Self‐assembly curves and atomic force microscopy (AFM) observations showed that only ASC, PSC and C‐25 could self‐assemble into fibrils with D‐periodicity, but the reconstruction rate of C‐25 was lower. Besides, PSC had relatively higher resolution ratio compared with others. Overall, pepsin‐extracted collagen displayed higher solubility and better fibril‐forming capacity, having the potential of applying in biomaterials and food‐packaging materials. 相似文献
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78.
The genetic diversity of 5 populations of Jatropha curcas L. (Euphorbiaceae), a species cultivated in tropical countries and used in biodiesel production, was analyzed by amplified fragment length polymorphism (AFLP). Plants from distinct populations found in the State of São Paulo, Brazil, had their genetic diversity characterized by using three primer combinations. The number of polymorphic bands obtained reached 184 and the base pair length of bands ranged from 75 to 350, with average PIC values of 0.418. Accessions from the Aguas de Santa Barbara population presented the highest percentage of polymorphic loci (89.76%), followed by the populations of Catanduva (84.24%), Jales (80.98%), Jurucê (78.80%) and Taquaritinga (70.65%). Plants collected from the populations of Taquaritinga and Jales presented the smallest and highest genetic diversities, respectively, measured by using both Nei's genetic variability index (h = 0.2242 and 0.2973) and Shannon's index (I = 0.3359 and 0.4319). The results obtained indicated that 73.1% of genetic variability corresponds to intrapopulational variation and 26.8% to variation among populations. The clustering dendrogram using Jacquard showed four clusters. Three clusters with low genetic diversity grouped most of individuals collected in distinct regions (63.3% JU, 47.0% JA and 82.5% TA) and the fourth with the higher genetic diversity was composed with basically individuals collected in CA and AS, but it also had samples collected in JU, JA and TA, where it is possible to select individuals to be included in breeding programs. 相似文献
79.
Condition monitoring and fault diagnosis of rolling element bearings timely and accurately are very important to ensure the reliability of rotating machinery. This paper presents a novel pattern classification approach for bearings diagnostics, which combines the higher order spectra analysis features and support vector machine classifier. The use of non-linear features motivated by the higher order spectra has been reported to be a promising approach to analyze the non-linear and non-Gaussian characteristics of the mechanical vibration signals. The vibration bi-spectrum (third order spectrum) patterns are extracted as the feature vectors presenting different bearing faults. The extracted bi-spectrum features are subjected to principal component analysis for dimensionality reduction. These principal components were fed to support vector machine to distinguish four kinds of bearing faults covering different levels of severity for each fault type, which were measured in the experimental test bench running under different working conditions. In order to find the optimal parameters for the multi-class support vector machine model, a grid-search method in combination with 10-fold cross-validation has been used. Based on the correct classification of bearing patterns in the test set, in each fold the performance measures are computed. The average of these performance measures is computed to report the overall performance of the support vector machine classifier. In addition, in fault detection problems, the performance of a detection algorithm usually depends on the trade-off between robustness and sensitivity. The sensitivity and robustness of the proposed method are explored by running a series of experiments. A receiver operating characteristic (ROC) curve made the results more convincing. The results indicated that the proposed method can reliably identify different fault patterns of rolling element bearings based on vibration signals. 相似文献
80.
In this paper, we propose a novel approach for key frames extraction on human action recognition from 3D video sequences. To represent human actions, an Energy Feature (EF), combining kinetic energy and potential energy, is extracted from 3D video sequences. A Self-adaptive Weighted Affinity Propagation (SWAP) algorithm is then proposed to extract the key frames. Finally, we employ SVM to recognize human actions on the EFs of selected key frames. The experiments show the information including whole action course can be effectively extracted by our method, and we obtain good recognition performance without losing classification accuracy. Moreover, the recognition speed is greatly improved. 相似文献